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Tag Archives: bacteria

So just last night my twitter feed was abuzz with bacterial infection drama. The Frontline PBS show was doing a whole episode called “Hunting the Nightmare Bacteria” and based on the chatter I’d say they struck a nerve. Our antibiotic arsenal is failing us, and it’s crucial to figure out new ways to battle these organisms. Some of those things we might be able to learn from studying their biology, but in other cases their own enemies might help us out in finding new compounds that can be used against them. And boy am I glad researchers are looking for ways to combat bad bacteria.

Just as a coincidence I had planned to highlight PATRIC today. PATRIC is the Pathosystems Resource Integration Center, sometimes also called BRC for bacterial Bioinformatics Resource Center. Their goal is to support researchers who study infectious diseases by focusing on these pathogenic organisms. Go over there and open the “Organisms” tab to get a feel for the species they examine. They offer annotation details of these species, but also provide lots of analysis tools as well. You can learn more about them from their “about” page.

PATRIC is a integration portal (as the name implies) of data concerning disease-causing infectious bacteria. Or to put it in their words:

PATRIC is the Bacterial Bioinformatics Resource Center, an information system designed to support the biomedical research community’s work on bacterial infectious diseases via integration of vital pathogen information with rich data and analysis tools.

We mentioned PATRIC at the beginning of the year in a SNPpets. Also, recently I was speaking with a threat abatement specialist who was lamenting the lack of coordinated data on infectious bacteria genomes. I was sure there was such a site, so we checked our blog here and voila, sure enough, exactly what they needed.

PATRIC indeed coordinates a lot of different types of data from disease-causing infectious bacteria. This includes data from all NIAID biodefense A/B/C pathogens. This includes hundreds of genomes from many isolation sources. For example, as of this writing there are nearly 500 genomes, including 57 complete, of Escherichia. In addition to genomic data, there are many other types of data including phylogenetic, host-pathogen protein-protein interactions, protein, pathways and more. One interesting feature, of many, is the disease map (for mycobacterium only right now) that shows local outbreaks and alerts. There are many tools to access and analyze this data from specialized searches to browsers.

Mike the Mad Biologist points to a nice article that describes aspects of the next-generation sequencing technologies with some helpful animations to illustrate the different styles. Mike goes on to describe that the sequencing itself isn’t the rate limiting step–the assembly and analysis steps are the hurdles really.

This data is turning up in databases now (see this ENCODE data at the UCSC Genome Browser as just one example), and will continue to flood in at dramatic rates. And the same technologies are being used for analysis of other aspects of biology (not just sequencing new species and individuals)–such as promoter binding or nucleosome positioning or RNA protein binding. So it is worth taking a look at the underlying technology to understand what’s being sequenced.

Being summer, a strangely slow connection and some other factors, I am embedding a talk from Doug Ramsey (posted on SciVee) on the GEBA project at JGI (instead of doing a tip myself :). The GEBA project recognizes that many, if not most, of the bacterial and archaeal genomes that have been sequenced to date have some relevance to human disease or other human interest. This of course is reasonable, but it also leads to big gaps in our knowledge of bacterial evolution and genomics, knowledge that would help us better understand those genomes that we find relevant and knowledge that in and of itself can be quite interesting and potentially useful. View the talk to learn more about this project to sequence 100 phylogenetically diverse bacterial and Archaeal genomes.
I’m also posting this as an introduction to JGI’s Adopt a Genome project. This project allows student groups to adopt and study a bacteria in the GEBA project and hopefully add to our knowledge and annotations of the genome while learning. The students can then annotate the adopted genome by using IMG-ACT.

Hey, say you’ve got a bacterial genome you just sequenced in your spare time (hey, the way technology is going, it’s not far off) and you need to do a quick and dirty annotation to get you started. Well, there are several tools out there to do that, predict genes, annotate regions, etc. I’d like to show you one in this tip that you might not have thought of but could be a useful tool to get started. It’s GATU (Genome Annotation Transfer Utility) at VBRC. As the name suggests, this doesn’t do any major gene predicting, what it does is take your genome and compare it to a closely related genome (the closer the better of course) and transfers all the annotation from the characterized genome. This is from a viral resource (VBRC) but it works just as well with bacterial genomes, something that might not have been obvious and puts another tool in your belt.

This week’s tip introduces a nice feature and tool of the Viral Bioinformatics Resource Center (VBRC). There are a lot of great tools at the VBRC to search and analyze hundreds of viral genomes. Most, if not all, of the tools can be used for searching and analyzing bacterial genomes also. The tool we are introducing in this tip is Base by Base. This tip actually came from a question from one of our readers in our weekly “WYP” feature a few weeks back. Reader Azalea asked:

I’m looking for a pairwise sequence alignment tool which can anchor specific nucleotides to be arbitrarily aligned.I just hope to fix certain positions to be aligned, which will change the whole alignment.

Chris Upton at VBRC suggested Base by Base. I’ve had the opportunity to use Base by Base and it’s a useful tool for working with pairwise alignments (could probably be used for any two sequences, not just bacterial and viral) and looks like a tool that Azalea might be able to use. Today’s tip shows you quickly how to add two sequences, align part by hand and select another region to align by algorithm (choice of T-Coffee, ClustalW or MUSCLE).

UCSC announced the Archaeal Genome Browser created by the Lowe Lab at UCSC last week. The browser has been accessible for a while, but this is the public ‘unveiling’ and announcement. The interface and use is very similar to the UCSC Genome Browser (free tutorial), though of course modified and geared to the analysis of Archaeal genomes. So add another resource and database to your toolbox, it looks like another good and useful one. As the announcement says:

Currently there are more than 50 completed archaeal genomes, the least studied domain of life. Although archaea and bacteria are both prokaryotes, often co-existing in the same environments, many aspects of archaeal cell biology such as DNA replication, repair, transcription, and translation are homologous to those found in eukaryotes. Some members of archaea are also notable for inhabiting extreme environments, including boiling terrestrial hot springs, black smoker vents at the bottom of the ocean, the ultra briny water of the Dead Sea, and highly acidic drainage water from ore mines, to name a few.

I’m currently at the third annual JGI Users Meeting titled Genomics of Energy and Environment. The first workshop is about IMG and when it finishes I’ll update you on anything new or interesting. A later session is on Biomass Feedstocks (for energy production), so look in this post for updates on that to. I’ll be updating every few hours.Edit (by Mary): for those of us who can’t be there at the workshop, the online tutorial is available: Integrated Microbial Genomes (IMG)Continue reading →

Came across a nice bacterial genome browser today via “Discovering Biology in a Digital World:” the Genome Projector. The is a map of over 100 bacterial genomes including a circular genome map, a genome map, a pathways map and a “DNAWalk” map. Put in a search term (I put “iron” in here, you know, as in ‘mining for,’ tried gold, but alas.. there is no gold in them thar… anyway…) and the hits show up as numbers in the tabs and pins in the maps. The maps are zoomable (just like GoogleMaps) and the pins are clickable with a popup to links out to databases and more information. It’s not quite as useful or in depth as perhaps IMG as a browser or Reactome or Kegg for pathways, but it’s simple and cool way to browse the genomes for more information and links to databases. Below the fold (continue reading link) are two more screenshots of my search in pathways and zoomed with clicked pin. Continue reading →

Recently I was watching a show about the beginning of life on Earth, and they were talking about how important Cyanobacteria was for making oxygen available for other life forms. As they talked about astrobiology and the search for other inhabitable planets, it occurred to me that I know a way of searching for microbes associated with such studies, or a variety of other categories for that matter, different than through a mere keyword search of PubMed. For my tip of the week, I want to show you how to use the Integrated Microbial Genomes (IMG) system to search for microbes associated with some basic characteristic or relevance, such as acid loving or causing disease.